Biology subjects

Danino, T.

Publications and source records attributed to Danino, T..

21 records · Page 2Linked to original sources

bioRxiv2019

A spatial cell culture model for predicting chemotherapy dosing strategies

Predicting patient responses to chemotherapy regimens is a major challenge in cancer treatment. To do this requires quantitative mathematical models to predict optimal dose and frequency for a particular drug, and experimental model systems such as three-dimensional organoids that accurately recapitulate the tumor microenvironment and heterogeneity. However, tracking the spatial dynamics of multiple cell types in three-dimensions can be a significant challenge in terms of time and throughput. Here we develop a two-dimensional system that allows for simple tracking of cell populations via fluorescence microscopy for modeling spatial dynamics in tumors. We first develop multiple 4T1 breast cancer cell lines resistant to varying concentrations of doxorubicin, and demonstrate how well mixed and spatially heterogeneous populations expand in a two-dimensional colony. We subject cell populations to varied dose and frequency of chemotherapy and measure colony growth radius and populations. We then build a mathematical model to describe the dynamics of both chemosensitive and chemoresistant populations, where we determine which number of doses can produce the smallest tumor size based on parameters in the system. In the future, this system can be adapted to quickly optimize dosing strategies in the setting of heterogeneous cell types or patient derived cells with varied chemoresistance.

cancer biology↗

bioRxiv2018

Rapid screening of engineered microbial therapies in a 3-D multicellular model

Synthetic biology is transforming therapeutic paradigms by engineering living cells and microbes to intelligently sense and respond to diseases including inflammation1,2, infections3-5, metabolic disorders6,7, and cancer8,9. However, the ability to rapidly engineer new therapies far outpaces the throughput of animal-based testing regimes, creating a major bottleneck for clinical translation10,11. In vitro approaches to address this challenge have been limited in scalability and broad-applicability. Here, we present a bacteria-in-spheroid co-culture (BSCC) platform that simultaneously tests host species, therapeutic payloads and synthetic gene circuits of engineered bacteria within multicellular spheroids over a timescale of weeks. Long-term monitoring of bacterial dynamics and disease progression enables quantitative comparison of critical therapeutic parameters such as efficacy and biocontainment. Specifically, we screen S. typhimurium strains expressing and delivering a library of antitumor therapeutic molecules via several synthetic gene circuits. We identify novel candidates exhibiting significant tumor reduction and demonstrate high similarity in their efficacies using a syngeneic mouse model. Lastly, we show that our platform can be expanded to dynamically profile diverse microbial species including L. monocytogenes, P. mirabilis, and E. coli in various host cell types. This high-throughput framework may serve to accelerate synthetic biology for clinical applications and understanding the host-microbe interactions in disease sites.

synthetic biology↗

bioRxiv2018

Two new plasmid post-segregational killing mechanisms for the implementation of synthetic gene networks in E. coli

Plasmids are the workhorse of both industrial biotechnology and synthetic biology, but ensuring they remain in bacterial cells is a challenge. Antibiotic selection, commonly used in the laboratory, cannot be used to stabilise plasmids in most real-world applications, and inserting dynamical gene networks into the genome is difficult. Plasmids have evolved several mechanisms for stability, one of which, post-segregational killing (PSK), ensures that plasmid-free cells do not grow or survive. Here we demonstrate the plasmid-stabilising capabilities of the axe/txe two component system and the microcin-V system in the probiotic bacteria Escherichia coli Nissle 1917 and show they can outperform the hok/sok system commonly used in biotechnological applications. Using plasmid stability assays, automated flow cytometry analysis, mathematical models and Bayesian statistics we quantified plasmid stability in vitro. Further, we used an in vivo mouse cancer model to demonstrate plasmid stability in a real-world therapeutic setting. These new PSK systems, plus the developed Bayesian methodology, will have wide applicability in clinical and industrial biotechnology.

synthetic biology↗